pysimdjson

Its magic function wrapping comes at a cost, trading ease of use for runtime performance. When you have a single C++ function to call that will run for a "long" time, pybind all the way. But pysimdjson tends to call a single function very quickly, and the overhead of a single function call is orders of magnitude slower than with cython when being explit with types and signatures. Wrap a class in pybind11 and cython and compare the stack trace between the two, and the difference is startling. Ex: https://github.com/TkTech/pysimdjson/issues/73

There is a Python wrapper for simdjson: https://github.com/TkTech/pysimdjson It looks like pysimdjson's biggest performance gain compared to e.g. orjson is when you can cherry-pick single values out of the JSON and avoid deserializing the whole document.

Not sure if it's quality, but I found this: https://github.com/TkTech/pysimdjson

This is the main bottleneck in pysimdjson[1]. 95-99%[2] of the time is spent creating Python objects rather than parsing the documents. There was no trick I could find (although treating all strings as bytes instead of using PyUnicode_DecodeUTF8/unicode_decode_utf8 was a fairly large gain on string-heavy documents) to reduce the cost of bringing the document into Python land, so I added a quick hack to push the filtering down into C, since most of my use cases only need a small part of the full document. [1]: https://github.com/TkTech/pysimdjson [2]: https://github.com/TkTech/pysimdjson/issues/22